Control and Dynamic Systems V31: Advances in Aerospace Systems Dynamics and Control Systems Part 1 of 3 - 1st Edition - ISBN: 9780120127313, 9780323162395

Control and Dynamic Systems V31: Advances in Aerospace Systems Dynamics and Control Systems Part 1 of 3

1st Edition

Advances in Theory and Applications

Editors: C.T. Leonides
eBook ISBN: 9780323162395
Imprint: Academic Press
Published Date: 28th November 1989
Page Count: 278
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Control and Dynamic Systems: Advances in Theory in Applications, Volume 31: Advances in Aerospace Systems Dynamics and Control Systems, Part 1 of 3 deals with significant advances in technologies which support the development of aerospace systems. It also presents several algorithms and computational techniques used in complex aerospace systems. The techniques discussed in this volume include: moving-bank multiple model adaptive estimation, algorithms for multitarget sensor tracking systems; algorithms in differential dynamic programming; optimal control of linear stochastic systems; and normalized predictive deconvulation. This book is an important reference for practitioners in the field who want a comprehensive source of techniques with significant applied implications.

Table of Contents



Moving-Bank Multiple Model Adaptive Estimation and Control Algorithms: An Evaluation

I. Introduction

II. Multiple Model Adaptive Estimation

III. Moving the Bank

IV. Adaptive Control

V. Performance Analysis on Simple Example

VI. Performance on Two-Bay Truss Model of Space Structure

VII. Summary


Centralized and Distributed Algorithms for Multitarget-Multisensor Tracking Systems

I. Introduction

II. Tracking a Single Target in Clutter

III. The Optimal Bayesian Filter and the Probabilistic Data Association Filter for a Single Target in Clutter

IV. Distributed Adaptive Estimation with Probabilistic Data Association

V. Tracking Multiple Targets in Clutter: The Joint Probabilistic Data Association Filter

VI. Distributed Tracking of Multiple Targets in Clutter: The Distributed Joint Probabilistic Data Association Filter

Appendix A . Gaussian Mixtures

Appendix B. Basic Fusion Techniques


Algorithms and Computational Techniques in Differential Dynamic Programming

I. Introduction

II. The Fundamental Differential Dynamic Programming Algorithm

III. Survey of Computational Methods for Differential Dynamic Programming

IV. The Theory

V. Research Directions


Minimax Estimation and Control of Multiplicative Systems

I. Introduction

II. Continuous-Time Systems

III. Discrete-Time Systems

IV. Conclusion


Reducing the Effects of Model Reduction Due to Parameter Variations

I. Introduction

II. Effects of Model Reduction Due to Parameter Variations

III. Hung and Han's Methods

IV. Lin and Han's Method

V. Reducing the Effects of Model Reduction on Stability Boundaries and Limit-Cycle Characteristics

VI. Model Reduction for Sampled-Data Control Systems with Parameter Variations

VII. Concluding Remarks


Absolute Stability and Robust Discrete Adaptive Control of Multivariable Systems

I. Introduction

II. The Absolute Stability Problem in Discrete-Time Systems

III. Robust Discrete Adaptive Control in (Not Strictly) Proper Systems

IV. Stability Analysis

V. Examples

VI. Conclusions

Appendix A. Proof of Lemma 1

Appendix B. Proof of Lemma 2

Appendix C. Proof of Lemma 3

Appendix D. Proof of Theorem 1

Appendix E. Implicit Equations (45)-(52)

Appendix F The Difference ∆V(t) in Equation (62)

Appendix G. The Role of the Minimal Gain K0


Optimal Control of Linear Stochastic Systems with Process and Observation Time Delays

I. Introduction

II. Problem Definition

III. Problem Formulation and Solution

IV. Practical Applications

V. Summary


Normalized Predictive Deconvolution: Multichannel Time-Series Applications to Human Dynamics

I. Introduction

II. The Human Dynamics Modeling Problem

III. Time Series and Entropy Models

IV. Normalized Predictive Deconvolution

V. Case Studies

VI. Conclusions




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© Academic Press 1989
Academic Press
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About the Editor

C.T. Leonides

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